Teaching
Student Research and Mentoring
Mentoring undergraduate research is an important part of my teaching. I work with students on projects involving statistical modeling, simulation, data analysis, and scientific communication, with an emphasis on helping students take ownership of the full research process. Several of these projects have led to external recognition and competitive research opportunities.
- Aditi Singh — Third Place, 2022 CAUSE/ASA Undergraduate Statistics Research Project Competition, Computational Analysis Of The Transformation Of Former Colonial Countries.
- Mark Raney — 2022 Anderson Science Summer Research Scholar, Assessing the similarity of countries’ COVID-19 experiences via time-series clustering.
- Riley Coburn — 2022 Anderson Science Summer Research Scholar, Change Point Detection with Dynamic Linear Modeling on COVID-19 Time Series Data.
- Yuhan Fu — 2022 Denison University Research Foundation, Bayesian Online Changepoint Detection on COVID-19 Data and Policy Analysis.
- Minh Le, Andrew Nguyen, and Dong Dong — Third Place, 2025 CAUSE/ASA Undergraduate Statistics Class Project Competition, A Decade of Decline: Statistical Modeling of Bank of America's Physical Branch Closures.
- Long Kim — Presented How Far Does War Reach? Sequential Detection of Conflict-Language Spillover into Apolitical Reddit Communities at the 2026 International Workshop on Sequential Methodology
- Nemi Kapur — Presented Bayesian Online Changepoint Detection on COVID-19 Data and Policy Analysis at the 2026 International Workshop on Sequential Methodology
Courses Taught at Denison University
Featured Course
DA 380: Sequential Analysis
An introduction to statistical methods for data observed over time, including sequential testing, adaptive design, and changepoint detection. Designed for upper-level undergraduates and suitable as an introductory course for graduate students or students in related quantitative fields.
- DA 101 — Introduction to Data Analytics
- DA 200 — Data Analytics Colloquium
- DA/MATH 220 — Applied Statistics
- DA 301 — Practicum in Data Analytics
- DA 352 — Advanced Predictive Methods in Data Analytics
- DA 380 — Sequential Analysis
- DA 401 — Senior Capstone
Courses Taught at University of Connecticut
- STAT 3025 — Statistical Methods
- STAT 3445 — Mathematical Statistics